Bottom Line:
A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression.The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data.We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection.

Background: Quantitative RT-PCR is the method of choice for studying, with both sensitivity and accuracy, the expression of genes. A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression. Here, we propose a set of reference genes, of the phytopathogenic bacteria Dickeya dadantii and Pectobacterium atrosepticum, which are stable in a wide range of growth conditions.

Results: We extracted, from a D. dadantii micro-array transcript profile dataset comprising thirty-two different growth conditions, an initial set of 49 expressed genes with very low variation in gene expression. Out of these, we retained 10 genes representing different functional categories, different levels of expression (low, medium, and high) and with no systematic variation in expression correlating with growth conditions. We measured the expression of these reference gene candidates using quantitative RT-PCR in 50 different experimental conditions, mimicking the environment encountered by the bacteria in their host and directly during the infection process in planta. The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data. Finally, we demonstrated that the ortholog of lpxC and yafS in Pectobacterium atrosepticum also showed stable expression in diverse growth conditions.

Conclusions: We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection. Thus, these genes are considered suitable for use as reference genes for the normalization of real-time RT-qPCR data of the two main pectinolytic phytopathogenic bacteria D. dadantii and P. atrosepticum and, probably, of other Enterobacteriaceae. Moreover, we defined general criteria to select good reference genes in bacteria.

pone-0020269-g003: RT-qPCR results of the 10 candidate reference genes.Results are represented by boxplots of the Cq values, measured from quantitative real time RT-qPCR, for the first 32 growth conditions in duplicates (white, A), the 10 growth conditions with different carbon sources (grey, B), and the 6 growth conditions modulating the supercoiling state of DNA (black, C).

Mentions:
None of these 10 selected genes had been previously used to normalize expression data. To validate their use as reference genes, transcription profiling, using real-time RT-qPCR assays, was performed and the invariability expression of these ten genes was evaluated in the 32 experimental conditions previously tested in micro-arrays (with two biological replicates). The results are presented in Figure 2B. Since an equal quantity of total RNA was used in each reaction, we directly compared transcript abundances using quantitative Cycle results, previously known as the threshold cycle Ct, crossing point CP, or take-off point TOP [13]. For the ten genes, the Cq values ranged from 17.99 to 32.75. In accordance with the micro-arrays results, the lowest expressed genes are ABF-0018436 and ABF-0018449 with a mean Cq value of 30.56 and 30.09, respectively. The highest expressed gene is ABF-0017965 (lpxC) with a mean Cq of 18.10. Most of the genes showed low variation of their Cq values but this is not the case with ABF-0016418, the Cq values of which range from 19.36 to 25.98 (Figure 3). Hence this does not seem to be a good reference gene for the normalization of expression data in these growth conditions. In order to evaluate the stability of each candidate, and to discriminate between technical and biological variability, a total of 2×105 copies of GeneAmplimer pAW 109 RNA were added to the reverse transcriptional reaction mixture and used as a control of experimental efficiency (Applied Biosystems) [8], [10], [14]. Standard deviation of pAW expression level in the quantitative Cycle (Cq) was evaluated from the 64 reactions and a standard deviation of Cq (ΔCq) equal to 0.4 was obtained, showing weak technical variability in our samples. Except for ABF-0016418, with a ΔCq of 1.22, the ΔCq values of the candidate reference genes were comparable to those of pAW which means that the Cq variation observed could be attributed to technical variability.

pone-0020269-g003: RT-qPCR results of the 10 candidate reference genes.Results are represented by boxplots of the Cq values, measured from quantitative real time RT-qPCR, for the first 32 growth conditions in duplicates (white, A), the 10 growth conditions with different carbon sources (grey, B), and the 6 growth conditions modulating the supercoiling state of DNA (black, C).

Mentions:
None of these 10 selected genes had been previously used to normalize expression data. To validate their use as reference genes, transcription profiling, using real-time RT-qPCR assays, was performed and the invariability expression of these ten genes was evaluated in the 32 experimental conditions previously tested in micro-arrays (with two biological replicates). The results are presented in Figure 2B. Since an equal quantity of total RNA was used in each reaction, we directly compared transcript abundances using quantitative Cycle results, previously known as the threshold cycle Ct, crossing point CP, or take-off point TOP [13]. For the ten genes, the Cq values ranged from 17.99 to 32.75. In accordance with the micro-arrays results, the lowest expressed genes are ABF-0018436 and ABF-0018449 with a mean Cq value of 30.56 and 30.09, respectively. The highest expressed gene is ABF-0017965 (lpxC) with a mean Cq of 18.10. Most of the genes showed low variation of their Cq values but this is not the case with ABF-0016418, the Cq values of which range from 19.36 to 25.98 (Figure 3). Hence this does not seem to be a good reference gene for the normalization of expression data in these growth conditions. In order to evaluate the stability of each candidate, and to discriminate between technical and biological variability, a total of 2×105 copies of GeneAmplimer pAW 109 RNA were added to the reverse transcriptional reaction mixture and used as a control of experimental efficiency (Applied Biosystems) [8], [10], [14]. Standard deviation of pAW expression level in the quantitative Cycle (Cq) was evaluated from the 64 reactions and a standard deviation of Cq (ΔCq) equal to 0.4 was obtained, showing weak technical variability in our samples. Except for ABF-0016418, with a ΔCq of 1.22, the ΔCq values of the candidate reference genes were comparable to those of pAW which means that the Cq variation observed could be attributed to technical variability.

Bottom Line:
A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression.The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data.We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection.

Background: Quantitative RT-PCR is the method of choice for studying, with both sensitivity and accuracy, the expression of genes. A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression. Here, we propose a set of reference genes, of the phytopathogenic bacteria Dickeya dadantii and Pectobacterium atrosepticum, which are stable in a wide range of growth conditions.

Results: We extracted, from a D. dadantii micro-array transcript profile dataset comprising thirty-two different growth conditions, an initial set of 49 expressed genes with very low variation in gene expression. Out of these, we retained 10 genes representing different functional categories, different levels of expression (low, medium, and high) and with no systematic variation in expression correlating with growth conditions. We measured the expression of these reference gene candidates using quantitative RT-PCR in 50 different experimental conditions, mimicking the environment encountered by the bacteria in their host and directly during the infection process in planta. The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data. Finally, we demonstrated that the ortholog of lpxC and yafS in Pectobacterium atrosepticum also showed stable expression in diverse growth conditions.

Conclusions: We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection. Thus, these genes are considered suitable for use as reference genes for the normalization of real-time RT-qPCR data of the two main pectinolytic phytopathogenic bacteria D. dadantii and P. atrosepticum and, probably, of other Enterobacteriaceae. Moreover, we defined general criteria to select good reference genes in bacteria.